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Road traffic crashes and emergency response optimization: a geo-spatial analysis using closest facility and location-allocation methods / Sulaiman Yunus in Geomatics, Natural Hazards and Risk, vol 13 (2022)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 13 (2022) . - pp 1535 - 1555 Titre : Road traffic crashes and emergency response optimization: a geo-spatial analysis using closest facility and location-allocation methods Type de document : Article/Communication Auteurs : Sulaiman Yunus, Auteur ; Ishaq A. Abdulkarim, Auteur Année de publication : 2022 Article en page(s) : pp 1535 - 1555 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] accident de la route [Termes IGN] allocation [Termes IGN] chemin le plus court, algorithme du [Termes IGN] distribution spatiale [Termes IGN] données localisées [Termes IGN] équipement sanitaire [Termes IGN] itinéraire [Termes IGN] Nigéria [Termes IGN] optimisation (mathématiques) [Termes IGN] réseau routier [Termes IGN] secours d'urgence Résumé : (auteur) Increased occurrence of road traffic crashes in Kano metropolis has resulted in a steady loss of lives, injuries, and increased people's risk exposure. This study looked into the emergency response to road traffic crashes in Kano, with a view to improving efficiency by developing linkages and synergy between Emergency Healthcare Facilities (EHCF), ambulances, and crash hotspots. The geographical location and attributes of the major EHCF, crash hotspots along highway intersections, and the two existent ambulances at the Kano State Fire Service (KSFS) and Federal Road Safety Corp head offices (FRSC) were obtained using GPS surveying. Road traffic network data (vector format) was digitized from satellite image, from which two major road classes (highways and minor roads) were identified, as well as their respective speed limits. The length and speed constraints were used to calculate time distances. Nearest Neighbor and Network (closest facility, shortest route, and location-allocation) analyses were carried out. Location-allocation analysis was to determine based on defined criteria the best locations to allocate EHCF or ambulance for optimum coverage. The results demonstrated that EHCF, ambulances, and crash places have different distribution patterns with almost no linkages. Closest ambulance facility analysis revealed the FRSC ambulance takes 9.41 minutes to arrive to crash spot 18 (Maiduguri Road, following NNPC) and 7.52 minutes to arrive at AKTH, the nearest EHCF. Comparatively, getting to Court road incident scene (spot 16) and IRPH as the closest EHCF takes about 3 times the time it takes to get to spot 18 and 4 times the time it takes to get to AKTH. This means that practically almost all victims in the city suffocate before reaching to the hospital. This signifies that, in cases of demand for CPR at the incident scene, there are higher likelihood of dying as it is expected to be provided within the first four minutes after the crash. Based on a maximum of 4 minutes impedance cutoff from all directions towards the occurrences areas, location-allocation analysis found eight new locations to maximize coverage and improve efficiency. It is concluded that current road traffic crash emergency response system has been determined to be ineffective. As a result, more ambulances should be strategically placed to improve emergency response times. Numéro de notice : A2022-884 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/19475705.2022.2086829 Date de publication en ligne : 16/06/2022 En ligne : https://doi.org/10.1080/19475705.2022.2086829 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102209 [article]